Use C# and a CNTK Neural Network To Predict House Prices In California

Building deep neural networks in C# has never been easier!

CNTK or the Cognitive Toolkit is Microsoft’s tensor library and answer to TensorFlow. It can build, train, and run many types of deep neural networks.

CNTK is fully compatible with .NET and C#. There’s no need to use Python, you can easily tap into the awesome power of deep neural networks using any NET language, including C#.

CNTK is super easy to use. Watch this, I’m going to build an app that can predict house prices in California using a deep neural network.

The first thing we need is a data file with house prices. The 1990 California cencus has exactly what we need.

If you want to follow along, download the California 1990 housing census and save it as california_housing.csv in your project folder.

The dataset is a CSV file with 17,000 records that looks like this:

The file contains information on 17k housing blocks all over the state of California:

• Column 1: The longitude of the housing block